Unlike the above works which assume that the association of users to the set of serving BSs is static, adopting a dynamic user association approach allows for more degrees of freedom and ensures connectivity and stable services for cell-edge users [1]}. In dynamic user clustering, the resource allocation per BS can be challenging as dynamic clustering requires more signaling overhead to establish new associations continuously. For example, the work in [1]} considers a joint clustering and beamforming design for maximizing network utility in HC-RAN under finite backhaul capacity per-BS constraints. Instead of using the backhaul constraint as a penalizing term as in [3]}, the authors in [1]} propose using the \(\ell _1\) -norm re-weighting technique for the constraint, coupled with the generalized weighted minimum mean square error (WMMSE) beamforming technique [5]}, [6]}. Similarly, the work in [7]} uses the proposed \(\ell _1\) -norm re-weighting technique for finite backhaul constraints and solves a sum-rate maximization problem over the beamforming and clustering strategies. By tackling the backhaul constraint using the \(\ell _1\) -norm re-weighting technique, the authors in [7]} use fractional programming techniques [9]}, [10]} to solve a sum-rate maximization problem.
